# Vision And YOLO

> Generated from `library/paper_cards/`. Do not edit this page directly; edit paper cards and rerun `vp run docs:generate`.

Object detection evolution, real-time perception, and visual candidate generation for dynamic command spaces.

## Paper Cards

| ID | Year | Status | Title |
| --- | ---: | --- | --- |
| [YOLO-001](/paper-library/cards/yolo-001) | 2016 | `extracted` | You Only Look Once: Unified, Real-Time Object Detection |
| [YOLO-002](/paper-library/cards/yolo-002) | 2017 | `extracted` | YOLO9000: Better, Faster, Stronger |
| [YOLO-003](/paper-library/cards/yolo-003) | 2018 | `extracted` | YOLOv3: An Incremental Improvement |
| [YOLO-004](/paper-library/cards/yolo-004) | 2017 | `extracted` | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks |
| [YOLO-005](/paper-library/cards/yolo-005) | 2014 | `extracted` | Microsoft COCO: Common Objects in Context |
| [YOLO-007](/paper-library/cards/yolo-007) | 2017 | `extracted` | Focal Loss for Dense Object Detection |
| [YOLO-009](/paper-library/cards/yolo-009) | 2020 | `extracted` | YOLOv4: Optimal Speed and Accuracy of Object Detection |
| [YOLO-010](/paper-library/cards/yolo-010) | 2022 | `extracted` | YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors |

## Use In SAH-BRI-Grasp

Use this page to locate source cards for evidence review. Promote claims through `library/EVIDENCE_MATRIX.md` before using them as manuscript-level claims.